Summary
2021
Session Number:PS2
Session:
Number:PS2-11
Dynamic Network Provisioning with Reinforcement Learning Based on Link Stability
Hong-Nam Quach, Sungwoong Yoem, Kyungbaek Kim,
pp.242-245
Publication Date:2021/9/8
Online ISSN:2188-5079
Summary:
Recently, with rising attention and widespread awareness of 5G technology, the rapid growth of mobile devices and various network infrastructures and services emerge. As means to provide responsive services and a guaranteed QoS level to individual demands while maintaining resource constraints, it is necessary to consider various factors affecting network service performance and dynamic network provisioning. In this paper, a Reinforcement Learning-based routing algorithm is proposed, which uses the information related to link stability to make routing decisions, called Reinforcement learning-based Routing with Link Stability (RRLS). To evaluate this algorithm, we applied the RRLS algorithm on a dynamic network provisioning framework and compared it to the RRLS algorithm and Dijkstra's algorithm. The result shows that the proposed algorithm performed better than Dijkstra's algorithm and shows that the proposed approach is an appealing solution for dynamic network provisioning routing.